Knowledge that Transforms

Richard A. Shick, James S. Trieschmann, Some Further Evidence on the Performance of Property-Liability Insurance Companies' Stock Portfolios, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 1 (Mar., 1978), pp. 157-166

Ever since Markowitz introduced the concept of portfolio theory in 1952, one of the questions predominant in the minds of financial theorists has been the constituency of the investor's optimal asset portfolio. Research into this area, which became known as capital market theory, attempted to analyze the equilibrium relationships between assets. One of the products of this research was the widely accepted Capital Asset Pricing Model (CAPM) of Sharpe and Lintner.

Glenn H. Petry, Russell J. Fuller, The Geographic Distribution of Papers at the Seven Academic Finance Associations in the United States, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 4, Proceedings of Thirteenth Annual Conference of the Western Finance Association, June 20-26, 1978 (Nov., 1978), pp. 785-794

In a series of recent articles ([2], [3], [4], [5]) R. B. Porter and his associates have conducted empirical comparisons of the Mean-Variance (EV) and Stochastic Dominance portfolio choice criteria. The basic methodology of all these studies was first to compute the set of EV-efficient portfolios by an optimizing algorithm, then to find through heuristic methods “stochastically dominant” portfolios, and finally to compare the two. A major finding of these studies was that most EV-efficient portfolios survived the second-degree stochastic dominance (SSD) test against the randomly generated portfolios. The purpose of this note is to show that, for all cases of practical interest, a portion of the EV frontier is a subset of the SSD-efficient set. In other words, we offer here an exact theoretical justification of some empirical results of the aforementioned studies.

According to a now classic study of stock market price behavior by Fama [6], the empirical distributions of daily log price relatives are usually stable Paretian, non-Gaussian. However, there appears to have been substantial reluctance to accept Fama's [6] research results as indicative of a fundamental return generating process which is stable Paretian, non-Gaussian. Blattberg and Gonedes [1], Clarke [4], Officer [18], Praetz [19], and Press [20] have each in their own way questioned the Fama [6] results. Most recently Hsu, Miller, and Wichern (HMW) [13] have suggested that in periods of homogeneous activity for a firm the empirical distribution of rates of return on a common share may be Gaussian, in other words, that the fundamental return generating process may be normal.

Roger G. Clarke, The Impact of a Fuel Adjustment Clause on the Regulated Firm's Value and Cost of Capital, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 4, Proceedings of Thirteenth Annual Conference of the Western Finance Association, June 20-26, 1978 (Nov., 1978), pp. 745-757

In many circles the Mean Variance Capital Asset Pricing Model (MV CAPM) is synonymous with the theory of capital asset pricing. But in a single-period discrete-time model which explicitly recognizes the existence of limited liability the derivation of the MV CAPM, if it is to be consistent with the von Neumann-Morgenstern postulates of rational behavior, must be based on the assumption that all investors have quadratic utility functions. This assumption in turn implies that risky assets are inferior goods. However, if we turn to the broader class of linear risk tolerance (LRT) utility functions, for which the separation property holds, other simple two-mutual-fund CAPMs can be derived. The power utility LRT CAPMs are of particular interest as they are consistent with risky assets being normal goods.

George G. C. Parker, Daniel Cooperman, Competitive Bidding in the Underwriting of Public Utility Securities, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 5 (Dec., 1978), pp. 885-902

In a timely, comprehensive article in this journal, Joy and Tollefson (J & T hereafter) treated design and interpretation problems for linear multiple discriminant analysis (LMDA). Although the article is generally correct in treating a complex topic, it has two problems:1. The (widely-used) split-sample validation technique that J & T used is an inappropriate method for establishing the efficacy of the estimated discriminant function.2. J & T reach erroneous conclusions on the correctness of two methods for assessing the discriminatory power of individual variables.This comment addresses these two problems.

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